A comparative study of dynamic contrast-enhanced MRI parameters as biomarkers for anti-angiogenic drug therapy.

The aim of the present study was to compare three tracer kinetics methods for the analysis of dynamic contrast-enhanced (DCE) MRI data, namely the generalized kinetics model, the distributed-parameter model and the initial area under the tumor tracer curve (IAUC) method, in a Phase I study of an anti-angiogenic drug ABT -869; and to explore their utility as biomarkers. Twenty-eight patients with a range of tumors formed the study population. DCE MRI performed at baseline and 2 weeks post-treatment was analyzed using all three methods, yielding percentage changes for various tracer kinetics parameters. Correlation analyzes were performed between these parameters and in relation to drug exposure. The association of these parameters with time-to-progression was examined using receiver-operating characteristic and Kaplan-Meier curves. Significant correlation with drug exposure was found for the following parameters: normalized IAUC (IAUC(norm)), fractional interstitial volume v(e), fractional intravascular volume v(1) and permeability PS. However, only v(e) and PS were effective in predicting late progression. A decrease in v(e) of more than 1.7% and a decrease in PS of more than 25.1% observed at 2 weeks post-treatment could be associated with late progression. All three tracer kinetics methods have biomarker potential for assessing the effects of anti-angiogenic therapy.

Post-treatment tumor gene expression signatures are more predictive of treatment outcomes than baseline signatures in breast cancer.

OBJECTIVE: Tumor gene expression signatures have been used to classify, prognosticate, and predict chemotherapy sensitivity in breast cancer, although almost all efforts have been focused on the unchallenged baseline tumor. Most cancer patients receive systemic therapy, and exposure to drug may modify the tumor's short-term and long-term outcomes. Drug-induced tumor gene signatures may thus be more predictive of treatment outcomes than the unperturbed tumor gene signatures. METHODS: Using a set of 47 breast cancer patients, we obtained paired prechemotherapy and postchemotherapy tumor biopsies and developed gene panels of baseline tumor (T1), postchemotherapy tumor (T2), and chemotherapy-induced relative change signatures (TDelta) to predict pathological response and progression-free survival (PFS). The signatures were validated in two independent test sets with paired prechemotherapy and postchemotherapy tumor samples, comprising of 18-20 patients each. RESULTS: T2 and TDelta were superior to T1 signatures in predicting for PFS (area under the curve of receiver operating characteristic 0.770 and 0.660 vs. 0.530) and pathological response (area under the curve of receiver operating characteristic 0.631 and 0.462 vs. 0.446) in the validation sets. In multivariate analysis for PFS with other clinical predictors, T2, but not T1, signatures remained as significant independent predictors. CONCLUSION: Postchemotherapy tumor gene signatures outperformed baseline signatures and clinical predictors in predicting for pathological response and PFS, independent of clinical and pathological response to chemotherapy. Drug-induced tumor gene signatures may be more informative than unchallenged signatures in predicting treatment outcomes. These findings challenge the current practice of relying only on the baseline tumor to predict outcome, which overlooks the contributions of therapeutic interventions.

Phase I and biomarker study of ABT-869, a multiple receptor tyrosine kinase inhibitor, in patients with refractory solid malignancies.

PURPOSE: To determine the safety and tolerability of ABT-869 at escalating doses and its effects on biomarkers relevant for antiangiogenic activity in patients with solid malignancies. PATIENTS AND METHODS: Patients with solid malignancies refractory to or for which no standard effective therapy exists were enrolled onto escalating-dose cohorts and treated with oral ABT-869 once daily continuously. RESULTS: Thirty-three patients were studied at doses of 10 mg/d, 0.1 mg/kg/d, 0.25 mg/kg/d, and 0.3 mg/kg/d. Dose-limiting toxicities in the first cycle (21 days) included grade 3 fatigue in a patient at 10 mg/d, grade 3 proteinuria and grade 3 hypertension in two separate patients at 0.25 mg/kg/d, and grade 3 hypertension and grade 3 proteinuria in two separate patients at 0.3 mg/kg/d, which was the maximum-tolerated dose. Other significant treatment-related adverse events included asthenia, hand and foot blisters, and myalgia. Oral clearance of ABT-869 was linear, with a mean of 2.7 +/- 1.2 L/h and half-life of 18.4 +/- 5.7 hours, with no evidence of drug accumulation at day 15. Two patients with lung cancer and one patient with colon cancer achieved partial response. Stable disease for more than four cycles was observed in 16 patients (48%). Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) showed dose-dependent reduced tumor vascular permeability that correlated with drug exposure. By day 15 of treatment, circulating endothelial cells were significantly reduced (P = .007), whereas plasma vascular endothelial growth factor was increased (P = .004). CONCLUSION: ABT-869 by continuous once-daily dosing was tolerable at doses

Chemotherapy-induced tumor gene expression changes in human breast cancers.

OBJECTIVE: Studying chemotherapy-induced gene expression changes in vivo, which could provide insights into mechanisms of chemotherapy resistance. METHODS: We analyzed and compared tumor gene expression changes of about 38 500 genes before and 3 weeks after doxorubicin or docetaxel treatment in 47 breast cancer patients. RESULTS: By using the median expression level of each probe set as the parameter, less than 5% of genes were upregulated or downregulated by more than 50% after treatment with either drug. Doxorubicin and docetaxel concordantly induced 251 genes predominantly involved in protein and macromolecule metabolism (upregulated), and cell cycle and DNA/RNA metabolism (downregulated). Doxorubicin treatment resulted in coregulation of a cluster of 345 probe sets involved in focal adhesion, Jak-Stat signaling pathway, cell adhesion molecules, and natural killer cell mediated cytotoxicity, whereas docetaxel treatment resulted in coregulation of a cluster of 448 probe sets involved in focal adhesion, neurodegenerative disorders, sphingolipid metabolism, and cell cycle. Tumors that were intrinsically sensitive or resistant to doxorubicin or docetaxel evoked distinct gene expression changes in response to the drug; doxorubicin-resistant tumors upregulated genes that were enriched for ErbB signaling, ubiquitin-mediated proteolysis, TGF-beta signaling, and MAP-kinase signaling pathways, whereas docetaxel-resistant tumors upregulated genes that were enriched for focal adhesion and regulation of actin cytoskeleton. The drug-specific tumor gene expression changes were validated in independent in-vitro and in-vivo datasets. CONCLUSION: Gene expression alterations of breast cancer were specific to doxorubicin and docetaxel treatment, and yielded mechanistic insights into resistance to either drug. Gene expression analysis provides more global perspectives on resistance pathways that could be exploited for therapeutic selection.

Genotype of human carbonyl reductase CBR3 correlates with doxorubicin disposition and toxicity.

OBJECTIVES: Doxorubicin is a cytotoxic drug with potential for severe myelosuppression that is highly variable and poorly predictable. METHODS: We correlated CBR1 and CBR3 genotypes with the pharmacokinetics and pharmacodynamics of doxorubicin in 101 Southeast Asian breast cancer patients receiving first-line doxorubicin. RESULTS: A common CBR3 11G>A variant was associated with lower doxorubicinol area under the concentration-time curve (AUC)/doxorubicin AUC metabolite ratio (P=0.009, GG vs. AA; trend test, P=0.004), lower CBR3 expression in breast tumor tissue (P=0.001, GG vs. AA), greater tumor reduction (P=0.015, GG vs. AA), and greater percentage reduction of leukocyte and platelet counts at nadir (trend test, P < or = 0.03). Chinese and Malays had higher frequency of the CBR3 11G>A variant than Indians (P < or = 0.002). Another variant CBR3 730G>A was associated with higher doxorubicinol AUC (P=0.009, GG vs. AA) and CBR3 expression in breast tumor tissue (P=0.001, GG vs AA). CONCLUSION: Polymorphisms in CBR3 may explain interindividual and interethnic variability of doxorubicin pharmacokinetics and pharmacodynamics.

A phase I study of docetaxel with ketoconazole modulation in patients with advanced cancers.

PURPOSE: The aims were to determine the maximum tolerable dose (MTD) of docetaxel with CYP3A inhibition by ketoconazole, and to correlate the pharmacokinetics of docetaxel with midazolam phenotyping of CYP3A activity. METHODS: Forty-one patients with refractory metastatic cancers were treated with an escalating dose of intravenous docetaxel once in every 3 week of 10 mg/m(2), concurrently with oral ketoconazole 200 mg twice daily for 3 days starting 2 days before the administration of docetaxel. Midazolam phenotyping test with ketoconazole modulation was performed before the first cycle of docetaxel. Docetaxel and midazolam pharmacokinetics were compared to our previous study of docetaxel treatment without ketoconazole modulation. RESULTS: Neutropenia was the dose-limiting toxicity. The maximum tolerated dose was 70 mg with mean AUC at 70 mg similar to 75 mg/m(2) of docetaxel without ketoconazole. The plasma clearances of docetaxel and midazolam were reduced by 1.7- and 6-fold, respectively. The variability of midazolam AUC was reduced from 157 to 67%, but variability of docetaxel clearance was not reduced by CYP3A inhibition. Docetaxel clearance correlated with renal function and maximum concentration of ketoconazole, but not midazolam clearance or other variables of hepatic function. CONCLUSION: Fixed dosing was found to be feasible, without increased variability of clearance or neutrophil toxicity compared to BSA-based dosing. With ketoconazole modulation, docetaxel clearance correlated with renal function but not CYP3A phenotype.

Ketoconazole renders poor CYP3A phenotype status with midazolam as probe drug.

Drugs metabolized by cytochrome CYP3A isoenzymes have wide interindividual variability and normally distributed plasma clearance distributions. This makes precise dosing difficult to achieve clinically, which may compromise safe therapy. We hypothesized that with potent inhibition of CYP3A, we could clinically render patients "poor metabolizer" phenotype status, and thus reduce interindividual pharmacokinetic variability of midazolam, a well-known CYP3A substrate. Intravenous bolus midazolam at doses of 2.5 mg and 1 mg were administered to 28 and 29 patients with cancer with and without co-administration of 200 mg of oral ketoconazole twice per day respectively for 3 days, starting 1 day before midazolam. Pharmacokinetic analyses of midazolam on both groups were derived using noncompartmental methods and compared. The mean clearance (CL) of midazolam was reduced 6 times by ketoconazole. Midazolam CL were normally distributed in both groups, and ranged from 1.7 to 51.9 and 1.4 to 8.2 L/hour in the control and ketoconazole groups, respectively, corresponding to a 7-fold reduction in dispersion between the 2 groups. Area-under-the-curve variability was reduced by >100%. A limited sampling model consisting of time points at 15 and 300 minutes was validated as a phenotype for CYP3A activity to facilitate the use of midazolam as a probe drug for CYP3A activity. Potent inhibition of CYP3A by ketoconazole reduced midazolam CL and area-under-the-curve variability, allowing for more precise achievement of therapeutic target drug exposure. Prospective evaluation of this approach, together with dose adjustment based on limited sampling, seems warranted.